文章基本信息

标题：FAST SUMMARIZATION OF LARGE-SCALE SOCIAL NETWORK USING GRAPH PRUNING BASED ON K-CORE PROPERTY
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作者：ANDRY ALAMSYAH ; YOGA PRIYANA ; BUDI RAHARDJO 等
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2017
卷号：95
期号：16
页码：3749
出版社：Journal of Theoretical and Applied
摘要：Graph based modelling is common in many implementation areas involving combinatorics relationship such as in social network. The data explosion produced from user generated content in online social network services trigger the emergence of large-scale social network. Having large graph at our disposal gives us many opportunity but at the same time increase the complexity problem, especially in several graph metric computations and also at graph visualization. A fast summarization methods is needed to reduce the graph size into the only most important pattern. This summarize sub-graph should represent the property or at least converge to the value of the original graph property. Social Network is characterized by scale free degree distributions, which have fat-head less important nodes that can be removed. Graph Pruning method is introduced to remove less important nodes in certain graph context, thus reduce the complexity of large-scale social network while still retain the original graph properties. The method is based on k-core graph properties. The paper show how is the effect of graph pruning to the several most used social network properties.
关键词：Social Network Analysis; Graph Pruning; Graph Theory; K-Core; Graph Sampling